The need for high-quality data in human resources

When many companies undertake efforts to collect more data and use it to improve their operations, they think of how they can use data externally. It's a tool for improving their marketing, fine-tuning their customer service strategies and making more sales. Rarely do they think about how they could use data internally.

This represents an area of potential growth for businesses. Just as they put a lot of time and money into mining information and ensuring data quality with their customers, companies can do the same with their workforce. They can collect information about their own employees and their productivity, and in so doing, they can improve their approach to human capital management.

According to The Wall Street Journal, one example is that companies can use data collection to reexamine their pay scales. Many businesses have predefined models for how much each employee is compensated, and these principles are guided by such criteria as productivity, seniority and other, more intangible, elements. Are their strategies logical? Data analysis might hold the answer.

Haig Nalbantian, a senior partner at consulting firm Mercer, told the Journal that predictive analytics could be the key to a more robust workforce in the years ahead. If companies can use their knowledge of past employee performance to project future productivity, they can fine-tune their strategies and pay workers at exactly the levels they deserve.

"[These analytics] absolutely will change how people get paid and the structure of their compensation - how much is fixed, how much is variable, how much is here and now versus how much is backloaded," Nalbantian said.

The debate is ongoing There is still some disagreement over how much impact data-driven analytics should have on the way companies pay their employees. Some are all for the data takeover, while others believe in tried-and-true strategies, such as the seniority-based salary hierarchy.

According to WA Today, there's a never-ending debate between proponents of old-school salary scales and new, data-driven approaches. Members of the latter faction are frustrated because to them, it seems like they're being paid less to perform the same work as their older counterparts.

"Why the 50 percent pay cut?" asked Tony Featherstone, a small business specialist with The Venture. "Is it fair that the same job - on paper - is suddenly only worth half the salary that previously came with it because the company is engaging in serious wage deflation?"

Companies may never fully settle the disagreement over pay scales among their ranks, but by collecting more information and working to ensure data quality, they can take a modest step forward.